
Organizing the world's information and making it universally accessible.
Software Engineer, Machine Learning Infrastructure, Google Cloud Platform
福利待遇
•无限假期
•Learning Budget
•育儿假
•医疗保险
必备技能
PyTorch
Apache Spark
Airflow
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
Responsibilities
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Create and deliver production solutions, best practice recommendations, tutorials, blog posts, and sample code for internal and external use.
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Work with early adopter customers. Provide customer and market feedback to product and engineering teams to help define product direction.
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Develop and deliver advanced enablement internally and externally.
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Work as part of an organization to contribute technical assets, prioritize and shape solution direction, while impacting business and bookings.
Minimum qualifications
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Bachelor's degree in Computer Science or a related engineering field, or equivalent practical experience.
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2 years of experience with programming in Python, C++, Java, or 1 year of experience with an advanced degree in an industry setting.
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2 years of experience with developing large-scale infrastructure, distributed systems or networks, or with compute technologies, storage or hardware architecture.
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1 year of experience with Machine Learning (ML) infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
Preferred qualifications
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Master's degree or PhD in Computer Science or a related technical field.
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5 years of experience in working with multiple enterprise and cloud technology systems, designing solutions, or developing business applications.
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Experience in one of the Large Language Model (LLM) frameworks (e.g., Ne Mo Megatron, Max Text, etc.).
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Experience with Kubernetes or Slurm.
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关于Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
员工数
Mountain View
总部位置
$1,700B
企业估值
评价
10条评价
4.5
10条评价
工作生活平衡
3.2
薪酬
4.3
企业文化
4.1
职业发展
4.2
管理层
3.8
82%
推荐率
优点
Great benefits and perks
Innovative and interesting work
Career development and learning opportunities
缺点
High pressure and expectations
Long hours and heavy workload
Fast-paced and overwhelming environment
薪资范围
57,503个数据点
Mid/L4
Mid/L4 · Accessibility Analyst
1份报告
$214,500
年薪总额
基本工资
$165,000
股票
-
奖金
-
$214,500
$214,500
面试评价
9条评价
难度
3.4
/ 5
时长
14-28周
录用率
44%
体验
正面 0%
中性 56%
负面 44%
面试流程
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
最新动态
Our eighth generation TPUs: two chips for the agentic era - blog.google
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1w ago
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9to5Google
News
·
1w ago
Google to invest up to $40 billion in AI rival Anthropic - Reuters
Reuters
News
·
1w ago
Google to invest up to $40B in Anthropic in cash and compute - TechCrunch
TechCrunch
News
·
1w ago